Ewin Tang

662 total citations
14 papers, 216 citations indexed

About

Ewin Tang is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics and Statistical and Nonlinear Physics. According to data from OpenAlex, Ewin Tang has authored 14 papers receiving a total of 216 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 6 papers in Atomic and Molecular Physics, and Optics and 4 papers in Statistical and Nonlinear Physics. Recurrent topics in Ewin Tang's work include Quantum Computing Algorithms and Architecture (10 papers), Quantum Information and Cryptography (6 papers) and Quantum many-body systems (5 papers). Ewin Tang is often cited by papers focused on Quantum Computing Algorithms and Architecture (10 papers), Quantum Information and Cryptography (6 papers) and Quantum many-body systems (5 papers). Ewin Tang collaborates with scholars based in United States, Hungary and Netherlands. Ewin Tang's co-authors include Robin Kothari, Jeongwan Haah, András Gilyén, Zhao Song, Chunhao Wang, Ankur Moitra, Tongyang Li, Ryan O’Donnell, Seth Lloyd and Allen P. Liu and has published in prestigious journals such as Physical Review Letters, Nature Physics and Journal of the ACM.

In The Last Decade

Ewin Tang

13 papers receiving 204 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ewin Tang United States 9 174 93 42 17 11 14 216
Changpeng Shao United Kingdom 9 204 1.2× 71 0.8× 60 1.4× 12 0.7× 19 1.7× 24 242
Narendra N. Hegade Spain 6 170 1.0× 90 1.0× 38 0.9× 11 0.6× 13 1.2× 15 218
Zhikuan Zhao Switzerland 8 276 1.6× 96 1.0× 99 2.4× 9 0.5× 20 1.8× 11 301
Lennart Bittel Germany 2 256 1.5× 141 1.5× 51 1.2× 15 0.9× 12 1.1× 4 290
Hlér Kristjánsson United Kingdom 4 228 1.3× 110 1.2× 31 0.7× 15 0.9× 21 1.9× 5 255
Elies Gil-Fuster Germany 5 244 1.4× 87 0.9× 43 1.0× 8 0.5× 16 1.5× 6 272
Elizabeth Crosson United States 6 154 0.9× 101 1.1× 23 0.5× 14 0.8× 7 0.6× 8 179
Bibek Pokharel United States 7 264 1.5× 195 2.1× 23 0.5× 29 1.7× 28 2.5× 14 318
Stavros Efthymiou Switzerland 7 145 0.8× 137 1.5× 20 0.5× 25 1.5× 11 1.0× 9 218
Meisheng Zhao China 5 205 1.2× 95 1.0× 80 1.9× 15 0.9× 12 1.1× 19 237

Countries citing papers authored by Ewin Tang

Since Specialization
Citations

This map shows the geographic impact of Ewin Tang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ewin Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ewin Tang more than expected).

Fields of papers citing papers by Ewin Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ewin Tang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ewin Tang. The network helps show where Ewin Tang may publish in the future.

Co-authorship network of co-authors of Ewin Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Ewin Tang. A scholar is included among the top collaborators of Ewin Tang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ewin Tang. Ewin Tang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
1.
Haah, Jeongwan, Robin Kothari, & Ewin Tang. (2024). Learning quantum Hamiltonians from high-temperature Gibbs states and real-time evolutions. Nature Physics. 20(6). 1027–1031. 17 indexed citations
2.
Moitra, Ankur, et al.. (2024). Structure Learning of Hamiltonians from Real-Time Evolution. 1037–1050. 4 indexed citations
3.
Liu, Allen P., et al.. (2024). High-Temperature Gibbs States are Unentangled and Efficiently Preparable. 1027–1036. 5 indexed citations
4.
Moitra, Ankur, et al.. (2024). Learning Quantum Hamiltonians at Any Temperature in Polynomial Time. 1470–1477. 8 indexed citations
5.
Haah, Jeongwan, Robin Kothari, Ryan O’Donnell, & Ewin Tang. (2023). Query-optimal estimation of unitary channels in diamond distance. 363–390. 11 indexed citations
6.
Gilyén, András, et al.. (2022). Sampling-based Sublinear Low-rank Matrix Arithmetic Framework for Dequantizing Quantum Machine Learning. Journal of the ACM. 69(5). 1–72. 15 indexed citations
7.
Tang, Ewin, et al.. (2022). Factorizations of $k$-nonnegative matrices. 13(2). 201–250.
8.
Gilyén, András, Zhao Song, & Ewin Tang. (2022). An improved quantum-inspired algorithm for linear regression. Quantum. 6. 754–754. 25 indexed citations
9.
Haah, Jeongwan, Robin Kothari, & Ewin Tang. (2022). Optimal learning of quantum Hamiltonians from high-temperature Gibbs states. 135–146. 25 indexed citations
10.
Tang, Ewin. (2022). Dequantizing algorithms to understand quantum advantage in machine learning. Nature Reviews Physics. 4(11). 692–693. 15 indexed citations
11.
Tang, Ewin. (2021). Quantum Principal Component Analysis Only Achieves an Exponential Speedup Because of Its State Preparation Assumptions. Physical Review Letters. 127(6). 60503–60503. 75 indexed citations
12.
Gilyén, András, et al.. (2020). Quantum-Inspired Algorithms for Solving Low-Rank Linear Equation Systems with Logarithmic Dependence on the Dimension. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 9 indexed citations
13.
Tang, Ewin. (2018). A quantum-inspired classical algorithm for recommendation systems. arXiv (Cornell University). 25. 128–228. 5 indexed citations
14.
Tang, Ewin. (1983). A CLASS OF NORMAL TRANSFORMATION OF THE EIGENVALUE PROBLEMS. JUSTC. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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